Reducing the risk of oil spill disasters is essential for protecting the environment and reducing economic losses. Oil spill surveillance constitutes an important component of oil spill disaster management. Advances in remote sensing technologies can help to identify parties potentially responsible for pollution and to identify minor spills before they cause widespread damage. Due to the large number of sensors currently available for oil spill surveillance, there is a need for a comprehensive overview and comparison of existing sensors. Specifically, this paper examines the characteristics and applications of different sensors. A better understanding of the strengths and weaknesses of oil spill surveillance sensors will improve the operational use of these sensors for oil spill response and contingency planning. Laser fluorosensors were found to be the best available sensor for oil spill detection since they not only detect and classify oil on all surfaces but also operate in either the day or night. For example, the Scanning Laser Environmental Airborne Fluorosensor (SLEAF) sensor was identified to be a valuable tool for oil spill surveillance. However, no single sensor was able to provide all information required for oil spill contingency planning. Hence, combinations of sensors are currently used for oil spill surveillance. Specifically, satellite sensors are used for preliminary oil spill assessment while airborne sensors are used for detailed oil spill analysis. While satellite remote sensing is not suitable for tactical oil spill planning it can provide a synoptic coverage of the affected area.

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INTRODUCTIONPrecise point positioning (PPP) is a new positioning technology that has received increased interest from the GPS community. Different from the traditional differential positioning technique, which requires access to observations from one or more reference stations with known coordinates, PPP involves only a single receiver; therefore, it is easy to deploy and cost-effective. PPP is also different from the conventional point positioning technique since it aims for decimeter-to centimeter-level positioning accuracy using carrier-phase observations. To date, only limited investigations have been conducted. However, using precise satellite orbit and clock products from organizations contributing to the International GPS Service (IGS), including Natural Resources Canada (NRCan), PPP has demonstrated such a potential in stand-alone static and kinematic modes on a global scale, with centimeter-and decimeterlevel positioning accuracy, respectively [1 -3]. Similar results have also been presented recently in [4,5]. As precise GPS orbit and clock products continue to improve in precision and timeliness, and real-time phase-based wide-area /global ionospheric correction becomes available, PPP for real-time decimeter-to centimeter-level positioning and navigation accuracy will become possible in the near future.PPP processing relies on the use of carrier-phase observations, the most accurate observable available from GPS. However, accurate position estimates at the decimeter to centimeter level are obtainable only after the phase ambiguities have converged, if treated as float values, or resolved as integer values. Previous PPP processing methods are commonly based on traditional ionosphere-free combinations, whereby the ambiguities can be estimated only as float values. Typically, 30 min is required for the float ambiguity unknowns to converge in a static mode, while 1 -2 h is required in a kinematic mode. The time required for the ambiguity parameters to converge therefore becomes the limiting factor for the use of PPP techniques for real-time applications. Further improvements would require the development of integer ambiguity resolution algorithms for PPP processing, but the integer characteristics of the phase ambiguities cannot be exploited with existing PPP processing methods. This paper presents a PPP processing method based on a new observation model. The method has resulted in a further reduction in observation noise level; more important, the new model allows for exploitation of the integer characteristics of carrierphase ambiguities. The latter capability opens the door for the development of new algorithms for ambiguity resolution in PPP processing. A stochastic estimation procedure has also been proposed to facilitate more robust stochastic estimation and to shorten the ambiguity convergence time.The paper is organized as follows. A new observation model for PPP processing is first described. Error mitigation using precise GPS orbit and clock correction data is then outlined. For more precise stoch...

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The single-frequency precise point positioning (PPP) technique has attracted increasing attention due to its high accuracy and low cost. However, a very long convergence time, normally a few hours, is required in order to achieve a positioning accuracy level of a few centimeters. In this study, an approach is proposed to accelerate the single-frequency PPP convergence by combining quad-constellation global navigation satellite system (GNSS) and global ionospheric map (GIM) data. In this proposed approach, the GPS, GLONASS, BeiDou, and Galileo observations are directly used in an uncombined observation model and as a result the ionospheric and hardware delay (IHD) can be estimated together as a single unknown parameter. The IHD values acquired from the GIM product and the multi-GNSS differential code bias (DCB) product are then utilized as pseudo-observables of the IHD parameter in the observation model. A time varying weight scheme has also been proposed for the pseudo-observables to gradually decrease its contribution to the position solutions during the convergence period. To evaluate the proposed approach, datasets from twelve Multi-GNSS Experiment (MGEX) stations on seven consecutive days are processed and analyzed. The numerical results indicate that the single-frequency PPP with quad-constellation GNSS and GIM data are able to reduce the convergence time by 56%, 47%, 41% in the east, north, and up directions compared to the GPS-only single-frequency PPP.